Space exploration: The interstellar goal and Titan demonstration

Automated interstellar space exploration is reviewed. The Titan demonstration mission is discussed. Remote sensing and automated modeling are considered. Nuclear electric propulsion, main orbiting spacecraft, lander/rover, subsatellites, atmospheric probes, powered air vehicles, and a surface science network comprise mission component concepts. Machine, intelligence in space exploration is discussed

Testing the structure and process of personality using ambulatory assessment data : an overview of within-person and person-specific techniques

In the present article, we discuss the potential of ambulatory assessment for an idiographic study of the structure and process of personality. To this end, we first review important methodological issues related to the design and implementation of an ambulatory assessment study in the personality domain, including methods of ambulatory assessment, frequency of measurement and duration of the study, ambulatory assessment scales and questionnaires, participant selection, training and motivation, and ambulatory assessment hard- and software. Next, we provide a detailed outline of available analytical approaches that can be used to analyze the intensive longitudinal data generated by an ambulatory assessment study. By doing this, we hope to familiarize personality scholars with these methods and to provide guidance for their use in the field of personality psychology and beyond

An Exploratory Study of Forces and Frictions affecting Large-Scale Model-Driven Development

In this paper, we investigate model-driven engineering, reporting on an exploratory case-study conducted at a large automotive company. The study consisted of interviews with 20 engineers and managers working in different roles. We found that, in the context of a large organization, contextual forces dominate the cognitive issues of using model-driven technology. The four forces we identified that are likely independent of the particular abstractions chosen as the basis of software development are the need for diffing in software product lines, the needs for problem-specific languages and types, the need for live modeling in exploratory activities, and the need for point-to-point traceability between artifacts. We also identified triggers of accidental complexity, which we refer to as points of friction introduced by languages and tools. Examples of the friction points identified are insufficient support for model diffing, point-to-point traceability, and model changes at runtime.Comment: To appear in proceedings of MODELS 2012, LNCS Springe

A unified view of data-intensive flows in business intelligence systems : a survey

Data-intensive flows are central processes in today’s business intelligence (BI) systems, deploying different technologies to deliver data, from a multitude of data sources, in user-preferred and analysis-ready formats. To meet complex requirements of next generation BI systems, we often need an effective combination of the traditionally batched extract-transform-load (ETL) processes that populate a data warehouse (DW) from integrated data sources, and more real-time and operational data flows that integrate source data at runtime. Both academia and industry thus must have a clear understanding of the foundations of data-intensive flows and the challenges of moving towards next generation BI environments. In this paper we present a survey of today’s research on data-intensive flows and the related fundamental fields of database theory. The study is based on a proposed set of dimensions describing the important challenges of data-intensive flows in the next generation BI setting. As a result of this survey, we envision an architecture of a system for managing the lifecycle of data-intensive flows. The results further provide a comprehensive understanding of data-intensive flows, recognizing challenges that still are to be addressed, and how the current solutions can be applied for addressing these challenges.Peer ReviewedPostprint (author's final draft

maigesPack: A Computational Environment for Microarray Data Analysis

Microarray technology is still an important way to assess gene expression in molecular biology, mainly because it measures expression profiles for thousands of genes simultaneously, what makes this technology a good option for some studies focused on systems biology. One of its main problem is complexity of experimental procedure, presenting several sources of variability, hindering statistical modeling. So far, there is no standard protocol for generation and evaluation of microarray data. To mitigate the analysis process this paper presents an R package, named maigesPack, that helps with data organization. Besides that, it makes data analysis process more robust, reliable and reproducible. Also, maigesPack aggregates several data analysis procedures reported in literature, for instance: cluster analysis, differential expression, supervised classifiers, relevance networks and functional classification of gene groups or gene networks

Knowledge management driven leadership, culture and innovation success – an integrative model

Purpose - This article examines the relation between knowledge management (KM) driven leadership, culture and innovation success of knowledge-intensive small and medium sized companies. By building on the previously reported research on leadership, culture, innovation , and knowledge management, we synergistically integrate d KM-driven leadership and innovation success while exploring the meditational role of culture in that. Design/methodology/approach - A conceptual model comprising three constructs was developed, namely KM-driven leadership, culture and innovation-based success of the company. To examine the conceptual model , quantitative research was conducted among selected companies from the SMEs offering knowledge-intensive business services. The companies were contacted by telephone and interviews were carried out with 111 key informants. The data was later analysed with exploratory and confirmatory statistical methods. We applied structural equation modelling techniques (SEM) with M plus 7.2 software package to investigate the effects of KM-driven leadership on culture, and consequently its effect on innovation-based success of the company. To investigate the meditational role of culture between KM-driven leadership and innovation-based success of the company a post-hoc analysis was undertaken. Originality/value - On the basis of the previous studies analysis, the following research gap has been identified. How does leadership based on knowledge management influences the innovation success of companies and what is the role of culture in this relation? By answering this question, the study contributes to the building of literature on the above topic twofold. First, it analyses the influence of KM-driven leadership in the creation of organizational culture, which in turn contributes to the innovation success of the company. Second, this research pioneers in that it explores the meditational role of culture among KM-driven leadership and innovation success. The results of the mediation analysis confirm that culture fully mediates the relationship of KM-driven leadership with innovation success . Practical implications - The paper proves the relation between KM-oriented leadership, culture and innovation-based success of the company. The analysis of the conceptual model confirms that culture mediates the relationship of leadership with innovation success. It highly contributes to the understanding of these phenomena in the context of small and medium-sized companies offering knowledge-intensive business services - still a topic at its early stage of research. The study also shows that KM-oriented leadership is a very important factor helping in the achievement of innovation success by companies. The relationships examined indicate the potential areas on which SME managers and executives should concentrate to achieve better innovation results